Collection of forward and inverse Physics-Informed Neural Network (PINN) examples developed in the CMD Lab.
This repository contains a collection of PINN-based scripts and supporting files developed for studying forward and inverse problems governed by partial differential equations (PDEs).
The repository includes examples related to:
- 1D heat equation
- Allen–Cahn equation
- inverse PINN workflows
- elasticity / solid mechanics
- related data, figures, and trained weights
This repository serves as a working research codebase for exploring PINN methodologies across multiple benchmark and applied problems.